Persistent memory for AI coding agents
Agent-agnostic. Single binary. Zero dependencies.
Installation •
Engram Cloud •
Agent Setup •
Architecture •
Plugins •
Contributing •
Full Docs
engram /ˈen.ɡræm/ — neuroscience: the physical trace of a memory in the brain.
Your AI coding agent forgets everything when the session ends. Engram gives it a brain.
A Go binary with SQLite + FTS5 full-text search, exposed via CLI, HTTP API, MCP server, and an interactive TUI. Works with any agent that supports MCP — Claude Code, OpenCode, Gemini CLI, Codex, VS Code (Copilot), Antigravity, Cursor, Windsurf, or anything else.
Agent (Claude Code / OpenCode / Gemini CLI / Codex / VS Code / Antigravity / ...)
↓ MCP stdio
Engram (single Go binary)
↓
SQLite + FTS5 (~/.engram/engram.db)
Quick Start
Install
brew install gentleman-programming/tap/engram
Windows, Linux, and other install methods → docs/INSTALLATION.md
Setup Your Agent
| Agent |
One-liner |
| Claude Code |
claude plugin marketplace add Gentleman-Programming/engram && claude plugin install engram |
| OpenCode |
engram setup opencode |
| Gemini CLI |
engram setup gemini-cli |
| Codex |
engram setup codex |
| VS Code |
code --add-mcp '{"name":"engram","command":"engram","args":["mcp"]}' |
| Cursor / Windsurf / Any MCP |
See docs/AGENT-SETUP.md |
Full per-agent config, Memory Protocol, and compaction survival → docs/AGENT-SETUP.md
That's it. No Node.js, no Python, no Docker. One binary, one SQLite file.
How It Works
1. Agent completes significant work (bugfix, architecture decision, etc.)
2. Agent calls mem_save → title, type, What/Why/Where/Learned
3. Engram persists to SQLite with FTS5 indexing
4. Next session: agent searches memory, gets relevant context
Full details on session lifecycle, topic keys, and memory hygiene → docs/ARCHITECTURE.md
| Category |
Tools |
| Save & Update |
mem_save, mem_update, mem_delete, mem_suggest_topic_key |
| Search & Retrieve |
mem_search, mem_context, mem_timeline, mem_get_observation |
| Session Lifecycle |
mem_session_start, mem_session_end, mem_session_summary |
| Conflict Surfacing |
mem_judge, mem_compare |
| Utilities |
mem_save_prompt, mem_stats, mem_capture_passive, mem_merge_projects, mem_current_project |
Full tool reference with parameters → DOCS.md#mcp-tools-18-tools
Terminal UI
engram tui
Navigation: j/k vim keys, Enter to drill in, / to search, Esc back. Catppuccin Mocha theme.
Git Sync
Share memories across machines. Uses compressed chunks — no merge conflicts, no huge files.
Local SQLite remains the source of truth. Cloud integration is opt-in replication.
engram sync # Export new memories as compressed chunk
git add .engram/ && git commit -m "sync engram memories"
engram sync --import # On another machine: import new chunks
engram sync --status # Check sync status
Full sync documentation → DOCS.md
Cloud Integration (Opt-In Replication)
Cloud is optional. Local SQLite stays authoritative; cloud is replication/shared access only.
Recommended first path (local smoke):
docker compose -f docker-compose.cloud.yml up -d
engram cloud config --server http://127.0.0.1:18080
engram cloud enroll smoke-project
engram sync --cloud --project smoke-project
Cloud mode is always project-scoped (--project is required; engram sync --cloud --all is intentionally blocked).
Known repairable cloud sync/upsert/canonicalization failures keep the original error visible and recommend the explicit doctor/repair flow below; Engram never auto-applies repair from sync or autosync.
For blocked cloud sync, transport_failed, or legacy session directory repair, see Engram Cloud Troubleshooting.
If cloud sync stays blocked after doctor/repair, download the rescue helper and run the recommended exported-row repair:
tools/repair-missing-session-directory.sh --apply --interactive --fix-exported <project>
engram sync --cloud --project <project>
--fix-exported repairs local exported sessions[].directory and observations[] required fields that can still break the final push after doctor reports ready. For sequential legacy sync_mutations blockers, use tools/repair-missing-session-directory.sh --apply --interactive --all <project>.
After upgrading engram while an MCP client is already running:
engram setup claude-code
Then restart Claude Code so it reloads the Engram MCP subprocess and refreshed hook/config files. Updating the engram binary on disk does not replace an already-running stdio MCP process.
Upgrade flow for existing local databases (diagnose → repair → bootstrap → status):
engram cloud upgrade doctor --project smoke-project # read-only readiness check
engram cloud upgrade repair --project smoke-project --dry-run
engram cloud upgrade repair --project smoke-project --apply
engram cloud upgrade bootstrap --project smoke-project # resumable enroll + push + verify
engram cloud upgrade status --project smoke-project # stage/class/reason
See DOCS.md — Cloud upgrade flow for the full state machine.
For authenticated mode, upgrade flow, dashboard behavior, reason codes, and full runtime/env details:
Steps to Test (Beta — Phases 2+3+4)
Try the new memory-conflict-surfacing features in complete isolation from your existing engram setup. Docker uses non-default ports + a separate data dir + a beta-only token, so your prod cloud and ~/.engram/ are untouched. Cleanup is one command.
What's in the beta:
- 🔄 Cloud sync of conflict relations cross-machine
- 🔍
engram conflicts CLI + HTTP API for retroactive audit + scan
- 🧠
--semantic scan that uses your existing Claude Code or OpenCode CLI to catch vocabulary-different conflicts ("Hexagonal" ↔ "Ports and Adapters") — $0 if you're on a Pro/Max/Plus subscription
Setup (4 commands)
git clone https://github.com/Gentleman-Programming/engram.git engram-beta-repo
cd engram-beta-repo && git checkout feat/memory-conflict-surfacing-cloud-sync
docker compose -f docker-compose.beta.yml up -d
go build -o ./engram-beta ./cmd/engram
# Isolated env (does NOT touch ~/.engram or your prod cloud)
export ENGRAM_DATA_DIR=/tmp/engram-beta-data
export ENGRAM_CLOUD_SERVER=http://127.0.0.1:28080
export ENGRAM_CLOUD_TOKEN=beta-token-CHANGE-ME-please-32chars
mkdir -p "$ENGRAM_DATA_DIR"
Use cases
1️⃣ Phase 1 — Conflict detection on save (sanity)
./engram-beta save \
"Use Clean Architecture" \
"Layers: entities, use cases, adapters." \
--type architecture --project beta-test
./engram-beta save \
"Use Hexagonal Architecture" \
"Ports and adapters separate domain from infra." \
--type architecture --project beta-test
✅ Second save returns candidates[] with the first memory's id.
2️⃣ Phase 2 — Cloud sync of relations cross-machine
./engram-beta cloud enroll beta-test
./engram-beta sync --cloud --project beta-test
./engram-beta cloud status
# Simulate a "second machine"
ENGRAM_DATA_DIR=/tmp/engram-beta-data-2 ./engram-beta cloud enroll beta-test
ENGRAM_DATA_DIR=/tmp/engram-beta-data-2 ./engram-beta sync --cloud --project beta-test
ENGRAM_DATA_DIR=/tmp/engram-beta-data-2 ./engram-beta search "Architecture"
✅ The "second machine" sees memories synced from the first.
3️⃣ Phase 3 — Admin CLI + HTTP API
./engram-beta conflicts list --project beta-test
./engram-beta conflicts stats --project beta-test
./engram-beta conflicts scan --project beta-test --dry-run
./engram-beta conflicts scan --project beta-test --apply --max-insert 10
# In another terminal: ./engram-beta serve
curl -s "http://127.0.0.1:7437/conflicts?project=beta-test" | jq
✅ List/scan/stats return sensible data.
4️⃣ Phase 4 — Semantic LLM-judge (the killer feature) 🎯
export ENGRAM_AGENT_CLI=claude # or opencode
./engram-beta conflicts scan --project beta-test --semantic --apply \
--max-semantic 5 --concurrency 3 --yes
✅ Your agent's LLM judges semantic similarity. $0 if on a subscription.
5️⃣ The case keyword search NEVER catches
Vocabulary-different but semantically-conflicting:
./engram-beta save \
"Use Postgres for the user database" \
"Postgres 15 is our SQL store for users." \
--type architecture --project beta-test
./engram-beta save \
"We migrated to MongoDB last quarter" \
"Document store now backs the user collection. SQL is gone." \
--type decision --project beta-test
./engram-beta conflicts scan --project beta-test --semantic --apply \
--max-semantic 5 --yes
./engram-beta conflicts list --project beta-test --status judged
✅ The LLM detects supersedes / conflicts_with with high confidence — FTS5 alone would not, because "Postgres" and "MongoDB" share no words.
Cleanup (zero residue)
docker compose -f docker-compose.beta.yml down -v
rm -rf /tmp/engram-beta-data /tmp/engram-beta-data-2 ./engram-beta
Your production engram is fully untouched throughout.
Full guide + troubleshooting
→ docs/BETA_TESTING.md
→ Report feedback: issues with beta-phase-2-3-4 label
CLI Reference
| Command |
Description |
engram setup [agent] |
Install agent integration |
engram serve [port] |
Start HTTP API (default: 7437) |
engram mcp [--tools=PROFILE] |
Start MCP server (stdio transport) |
engram tui |
Launch terminal UI |
engram search <query> |
Search memories |
engram save <title> <msg> |
Save a memory |
engram timeline <obs_id> |
Chronological context |
engram context [project] |
Recent session context |
engram stats |
Memory statistics |
engram export [file] |
Export to JSON |
engram import <file> |
Import from JSON |
engram sync |
Git sync export/import |
engram cloud <subcommand> |
Opt-in cloud config/status/enrollment + cloud runtime (serve) |
engram projects list|consolidate|prune |
Manage project names |
engram obsidian-export |
Export to Obsidian vault (beta) |
engram version |
Show version |
Full CLI with all flags → docs/ARCHITECTURE.md#cli-reference
Documentation
Dashboard contributors: if you modify .templ files in internal/cloud/dashboard/, run make templ to regenerate before committing. See DOCS.md — Dashboard templ regeneration.
License
MIT
Inspired by claude-mem — but agent-agnostic, simpler, and built different.
Contributors